drug-discovery-prompts/upstream/K-Dense-AI-scientific-agent-skills/skills/liteparse/references/ocr_and_formats.md

title, task, lineage_type, upstream_source, upstream_sha, imported_at, prompt_class, upstream_changes, author, validated

title	task	lineage_type	upstream_source	upstream_sha	imported_at	prompt_class	upstream_changes	author	validated
OCR and Supported Input Formats		import	https://github.com/K-Dense-AI/scientific-agent-skills/blob/9c9bd2e9/skills/liteparse/references/ocr_and_formats.md	9c9bd2e9	2026-06-27	prompt	accepted	upstream	false

OCR and Supported Input Formats

Built-in OCR (Tesseract)

• Default: OCR enabled on parse.
• Engine: Tesseract bundled with the library (zero extra setup for typical English PDFs).
• Disable when PDFs have selectable text: --no-ocr or ocr_enabled=False.

lit parse document.pdf
lit parse document.pdf --ocr-language fra
lit parse document.pdf --no-ocr

parser = LiteParse(ocr_enabled=True, ocr_language="eng", num_workers=4)

Language codes

Use Tesseract codes (not ISO alone): eng, fra, deu, spa, chi_sim, etc. Map HTTP OCR language=en separately (see below).

Offline / air-gapped environments

Pre-download .traineddata files, then either:

export TESSDATA_PREFIX=/path/to/tessdata
lit parse document.pdf --ocr-language eng

or:

lit parse document.pdf --tessdata-path /path/to/tessdata

---

HTTP OCR servers (optional)

For higher accuracy or GPU-backed OCR, run a server implementing the LiteParse OCR API and point LiteParse at it:

lit parse document.pdf --ocr-server-url http://localhost:8080/ocr

parser = LiteParse(ocr_server_url="http://localhost:8080/ocr")

API contract (summary)

• POST {base_url}/ocr (typically http://host:8080/ocr)
• Content-Type: multipart/form-data
• Fields: file (image bytes, required), language (optional, ISO 639-1, default en)
• Response JSON:

{
  "results": [
    {
      "text": "recognized text",
      "bbox": [x1, y1, x2, y2],
      "confidence": 0.95
    }
  ]
}

• Origin top-left; bbox axis-aligned in pixels.
• Full spec: https://github.com/run-llama/liteparse/blob/main/OCR_API_SPEC.md

Reference server implementations (upstream repo)

• ocr/easyocr/ — EasyOCR wrapper
• ocr/paddleocr/ — PaddleOCR wrapper

You only need a server if you choose HTTP OCR; Tesseract is sufficient for many workflows.

---

Supported input formats

PDF (native)

.pdf — no conversion step.

Office documents (LibreOffice)

Requires LibreOffice installed and on PATH.

Type	Extensions
Word	.doc, .docx, .docm, .odt, .rtf, .pages
PowerPoint	.ppt, .pptx, .pptm, .odp, .key
Spreadsheets	.xls, .xlsx, .xlsm, .ods, .csv, .tsv, .numbers

Install LibreOffice:

# macOS
brew install --cask libreoffice

# Ubuntu/Debian
sudo apt-get install libreoffice

# Windows (Chocolatey)
choco install libreoffice-fresh

On Windows, add LibreOffice program directory to PATH (often C:\Program Files\LibreOffice\program).

Images (ImageMagick)

Requires ImageMagick.

Formats
.jpg, .jpeg, .png, .gif, .bmp, .tiff, .webp, .svg

Install ImageMagick:

# macOS
brew install imagemagick

# Ubuntu/Debian
sudo apt-get install imagemagick

# Windows
choco install imagemagick.app

---

Conversion pipeline

Office / image → (LibreOffice or ImageMagick) → PDF → PDFium extract → optional OCR → grid projection → text + JSON

If conversion fails, install the missing tool and retry. Plain-text-only paths cannot be screenshot-rendered.